Dataframe tranposition and mapping - pandas

Question

I need to perform two sample t-test, for which I have to transpose my sample file and map values from another csv file to the sample file. I am new to python, so far I have tried this:
with open('project.csv') as f_project:
df = pd.read_csv('project.csv', delimiter = ',', dtype= 'unicode',
error_bad_lines=False)
df.set_index('TaxID', inplace=True)
df_kraken = df.T
df_meta = pd.read_csv('Meta3251.csv', delimiter = ',', dtype= 'unicode',
error_bad_lines=False, usecols = ['SRA ID', '(0/1)'])
df_kraken['Meta'] = df_kraken['TaxID'].map(df_meta.set_index('SRA ID')
['(0/1)'])
My sample file dataframe after transposition looks like this:
333046 1049 337090
PRJEB3251_ERR169499 0.05 0.03 0.01
PRJEB3251_ERR169500 0 0 0
PRJEB3251_ERR169501 0 0 0
PRJEB3251_ERR169502 0.05 0 0
PRJEB3251_ERR169503 0.03 1.9 0
PRJEB3251_ERR169507 0.01 0 0
PRJEB3251_ERR169508 0 0.1 0
PRJEB3251_ERR169509 0 0.05 0
The index is not been set as TaxID.
I have another csv file which T have taken as another dataframe so that I can map the values. It looks like
SRA ID (0/1)
ERR169611 1
ERR169610 1
ERR169609 1
ERR169608 1
ERR169607 0
ERR169606 0
ERR169605 1
ERR169604 1
ERR169484 0
I need to map the zero one values to the first column of 1st dataframe. Im stuck with the error : KeyError: 'TaxID'
Any hepl regarding this will be highly appreciated.
After you suggestion I have this :
import pandas as pd
df = pd.read_csv('project.csv').set_index('ID').T
df = df.reset_index().rename(columns={'index': 'Project ID'})
df_meta = pd.read_csv('Meta3251.csv', delimiter = ',', dtype= 'unicode',
error_bad_lines=False, usecols = ['SRA ID', '(0/1)'])
df['KEY'] = df['Project ID'].str.split('_').str[1]
df['Meta ID'] = df['KEY'].replace(dict(zip(df_meta['SRA ID'], df['(Project
ID)'])))
df.to_csv('R.csv')
After this I have the following result:
Project ID 333046 1049 KEY Meta ID
0 PRJEB3251_ERR169499 0.05 0.03 ERR169499 PRJEB3251_ERR169636
1 PRJEB3251_ERR169500 0 0 ERR169500 PRJEB3251_ERR169635
2 PRJEB3251_ERR169501 0 0 ERR169501 PRJEB3251_ERR169626
3 PRJEB3251_ERR169502 0.05 0 ERR169502 PRJEB3251_ERR169625
I have the index but the good part is now im able to rename my column, the mapping is not working though.

Answer 1

Here a solution that could work:
df = pd.read_csv('project.csv', delimiter = ',', dtype= 'unicode', error_bad_lines=False)
df.set_index('TaxID', inplace=True)
df_kraken = df.T.reset_index() # Make sure 'TaxID' is a column
df_meta = pd.read_csv('Meta3251.csv', delimiter = ',', dtype= 'unicode', error_bad_lines=False, usecols = ['SRA ID', '(0/1)'])
# In your example the second dataframe only matches what's after the '_'
# so you can isolate that part
df_kraken['KEY'] = df_kraken['TaxID'].str.split('_').str[1]
df_kraken['Meta'] = df_kraken['KEY'].replace(dict(zip(meta['SRA'], meta['ID'])))
EDIT
The question has been edited.
After read_csv() (first line):
TaxID PRJEB3251_ERR169499 PRJEB3251_ERR169500 PRJEB3251_ERR169501
0 333046 0.05 0 0
1 1049 0.03 0 0
2 337090 0.01 0 0
3 288681 3.6 0 0
4 267889 0.02 0 0
...
Then
df = df.set_index('TaxID').T
print(df)
TaxID 333046 1049 337090
PRJEB3251_ERR169499 0.05 0.03 0.01
PRJEB3251_ERR169500 0.00 0.00 0.00
PRJEB3251_ERR169501 0.00 0.00 0.00
Note that at this point TaxID is the name of the columns index, not of the row index. If you want to have TaxID as a column:
df = df.reset_index().rename(columns={'index': 'TaxID'})
To avoid confusion you can remove TaxID from the column name:
df.columns.name = None